Update app.py

app.py

@@ -6,16 +6,17 @@ import librosa
 import numpy as np
 import re
 
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 processor = Wav2Vec2Processor.from_pretrained("the-cramer-project/Wav2vec-Kyrgyz")
 model = Wav2Vec2ForCTC.from_pretrained("the-cramer-project/Wav2vec-Kyrgyz")
-model.to("cuda")
+model.to(device = device)
 
 def transcribe(file_):
     arr_audio, _ = librosa.load(file_, sr=16000)
     inputs = processor(arr_audio, sampling_rate=16_000, return_tensors="pt", padding=True)
 
     with torch.no_grad():
-        logits = model(inputs.input_values.to("cuda"), attention_mask=inputs.attention_mask.to("cuda")).logits
+        logits = model(inputs.input_values.to(device = device), attention_mask=inputs.attention_mask.to(device = device)).logits
 
     pred_ids = torch.argmax(logits, dim=-1)
     text = processor.batch_decode(pred_ids)[0]